Engagement Manager (AI)
ΠΡΡΡ & Π‘ΠΎΠΏΡΠΎΠ²ΠΎΠ΄
ΠΠ»Ρ ΠΌΡΡΡΠ° Ρ ΡΡΠΎΠΉ Π²Π°ΠΊΠ°Π½ΡΠΈΠ΅ΠΉ Π½ΡΠΆΠ΅Π½ Plus
ΠΠΏΠΈΡΠ°Π½ΠΈΠ΅ Π²Π°ΠΊΠ°Π½ΡΠΈΠΈ
Location: Hybrid role based in San Francisco, New York, or Los Angeles, with in-office collaboration and travel to customer sites as required.
Salary: $160Kβ$220K OTE, plus equity.
Company
builds a data platform for machine learning applications, focused on reducing complexity, latency, and scale barriers.
What you will do
- Manage multiple defined-scope customer engagements from project planning through production deployment.
- Coordinate forward-deployed engineers, customer stakeholders, and partners.
- Maintain project plans, timelines, RAID logs, action items, status reports, and other governance materials.
- Track and escalate risks, issues, blockers, owners, and due dates.
- Translate between business and technical teams by capturing requirements and documenting decisions.
- Prepare executive briefings and contribute to discovery, planning, and engagement-playbook improvements.
Requirements
- 5+ years of experience in project or program management, professional services delivery, technical account management, or a comparable customer-facing delivery role.
- Experience managing cross-functional projects through completion.
- Strong organization, written communication, and follow-through.
- Comfort working with technical teams and customer stakeholders.
- Availability for hybrid in-office collaboration in San Francisco, New York, or Los Angeles.
- Ability to travel to customer sites as engagements require.
Nice to have
- Exposure to data, machine learning, artificial intelligence, or infrastructure and platform products.
- Familiarity with Linear, Jira, Asana, or similar project-management tools.
- Project-management coursework or certification, such as PMP.
- Experience in a startup or fast-paced environment.
Culture & Benefits
- Hands-on delivery role with opportunities to take on larger and more complex engagements.
- In-office collaboration combined with customer-site travel as needed.
- Equity compensation.
- Work focused on delivering machine-learning deployments that generate customer value.
ΠΡΠ΄ΡΡΠ΅ ΠΎΡΡΠΎΡΠΎΠΆΠ½Ρ: Π΅ΡΠ»ΠΈ ΡΠ°Π±ΠΎΡΠΎΠ΄Π°ΡΠ΅Π»Ρ ΠΏΡΠΎΡΠΈΡ Π²ΠΎΠΉΡΠΈ Π² ΠΈΡ ΡΠΈΡΡΠ΅ΠΌΡ, ΠΈΡΠΏΠΎΠ»ΡΠ·ΡΡ iCloud/Google, ΠΏΡΠΈΡΠ»Π°ΡΡ ΠΊΠΎΠ΄/ΠΏΠ°ΡΠΎΠ»Ρ, Π·Π°ΠΏΡΡΡΠΈΡΡ ΠΊΠΎΠ΄/ΠΠ, Π½Π΅ Π΄Π΅Π»Π°ΠΉΡΠ΅ ΡΡΠΎΠ³ΠΎ - ΡΡΠΎ ΠΌΠΎΡΠ΅Π½Π½ΠΈΠΊΠΈ. ΠΠ±ΡΠ·Π°ΡΠ΅Π»ΡΠ½ΠΎ ΠΆΠΌΠΈΡΠ΅ "ΠΠΎΠΆΠ°Π»ΠΎΠ²Π°ΡΡΡΡ" ΠΈΠ»ΠΈ ΠΏΠΈΡΠΈΡΠ΅ Π² ΠΏΠΎΠ΄Π΄Π΅ΡΠΆΠΊΡ. ΠΠΎΠ΄ΡΠΎΠ±Π½Π΅Π΅ Π² Π³Π°ΠΉΠ΄Π΅ β